Fig. 5: Comparison of prediction accuracy between genomic selection (GS) models incorporating multi-trait QTL identified by GWAS and traditional GS models (BRR, BayesA, and BayesC). | Communications Biology

Fig. 5: Comparison of prediction accuracy between genomic selection (GS) models incorporating multi-trait QTL identified by GWAS and traditional GS models (BRR, BayesA, and BayesC).

From: Genomic selection with GWAS-identified QTL markers enhances prediction accuracy for quantitative traits in poplar (Populus deltoides)

Fig. 5: Comparison of prediction accuracy between genomic selection (GS) models incorporating multi-trait QTL identified by GWAS and traditional GS models (BRR, BayesA, and BayesC).

“Model” represents the GS model without optimization, “Model + 10−5sig”, “Model + 10−4sig”, “Model + 10−3sig”, and “Model + 10−2sig” refer to the GS model integrated with multi-trait QTLs identified at P < 1 × 10−5, P < 1 × 10−4, P < 1 × 10−3, and P < 1 × 10−2, respectively. DBH diameter at breast height, BD basic density, Hemic hemicellulose, Cellu cellulose, BSD infection rate of black spot disease, LA leaf area, LL leaf length, LW leaf width, LVA leaf vein angle.

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